Data Science course in Lausanne

Lausanne
Full-time (9 weeks)

In 9 intensive weeks in Lausanne, learn all the skills of a Data Scientist. Analyse rich data sets, make complex decisions using data and discover the power of AI & Machine learning to solve real world problems.

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In 9 intensive weeks, learn Data Science from Python to advanced Machine Learning at Le Wagon.
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Upcoming batches
Apr 11, 2022 - Jun 10, 2022 Course in French (8,500 CHF)
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Oct 10, 2022 - Dec 9, 2022 Course in French (8,500 CHF)
Open - Apply now

We run Full Time Coding Bootcamps multiple times a year. Register to be notified as soon as the next batch is open for applications - Register here

Overview

Join an immersive Data Science course

Our Data Science course in Lausanne takes you from Data Enthusiast to Data Scientist in 9 weeks. You will be able to analyse data to make decisions, implement AI and Machine Learning models and build a practical data application ready for real-world deployment. Enter the world of Data Science as a Data Analyst, Data Engineer or Data Scientist, enhance your academic studies, solve global issues, or advance your career with our 600+ global hiring partners in industries such as marketing, finance, and commerce with a unique data skillset.

Le Wagon's Data Science course gives you the data science skills you need to launch your career in any data-related role.
Learn Data Science in 9 weeks
Check out what our alumni have built in 2 weeks
Curriculum

Our Data Science curriculum

Our course in Lausanne is designed to help you learn Data Science step by step. Use data to provide actionable insights and build a real-world data application to showcase your skills.

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Python for Data Science

Learn programming in Python, how to work with Jupyter Notebook and to use powerful Python libraries like Pandas and NumPy to explore and analyse big data sets. Collect data from various sources, including CSV files, SQL queries on relational databases, Google Big Query, APIs and Web scraping.

Relational Database & SQL

Learn how to formulate a good question and how to answer it by building the right SQL query. This module will cover schema architecture and then dive deep into the advanced manipulation of SELECT to extract useful information from a stand-alone database or using a SQL client software like DBeaver.

Data Visualization

Make your data analyses more visual and understandable by including data visualisations in your Notebook. Learn how to plot your data frames using Python libraries such as matplotlib and seaborn and transform your data into actionable insights.

Statistics, Probability, Linear Algebra

In Lausanne you will learn about the underlying math behind all the libraries and models used in the bootcamp. Become comfortable with the basic concepts of statistics & probabilities (mean, variance, random variable, Bayes’s Theorem, etc.) and with matrix computation, at the core of numerical operations in libraries like Pandas and Numpy.

c pulse Statistical inferences

You'll learn how to structure a Python repository with object-oriented programming in order to clean your code and make it re-usable, how to survive the data preparation phase of a vast dataset, and how to find and interpret meaningful statistical results based on multivariate regression models.

speaker Communication

Data analysts are meant to communicate their findings to non-technical audiences: You will learn how to create impact by explaining your technical insights and turn them into business decisions using cost/benefits analysis. You'll be able to share your progress, present and compare your results to your teammates.

Preprocessing and Supervised Learning

Learn how to explore, clean, and prepare your dataset through preprocessing techniques like vectorisation. Get familiar with the classic models of supervised learning - linear and logistic regressions. Learn how to solve prediction and classification tasks with the Python library scikit-learn using learning algorithms like KNN (k-nearest neighbors).

Generalisation and Overfitting

Implement training and testing phases to make sure your model can be generalised to unseen data and deployed in production with predictable accuracy. Learn how to prevent overfitting using regularization methods and how to chose the right loss function to improve your model's accuracy.

Performance Metrics

Evaluate your model's performance by defining what to optimise and the right error metrics in order to assess your business impact. Improve your model's performance with validation methods such as cross validation or hyperparameter tuning. Finally, discover a powerful supervised learning method called SVM (Support Vector Machines).

Unsupervised Learning & Advanced Methods

Move to unsupervised learning and implement methods like PCA for dimensionality reduction or clustering for discovering groups in a data set. Complete your toolbelt with ensemble method that combine other models to improve performance, such as Random Forest or Gradient Boosting.

Neural Networks

Unveil the magic behind Deep Learning by understanding the architecture of neural networks (neurons, layers, stacks) and their parameters (activations, losses, optimisers). Become autonomous to build your own networks, especially to work with images, times and text, while learning the techniques and tricks that make Deep Learning work.

Computer Vision

Go further into computer vision with Convolutional Neural Networks, architectures designed to make the most out of images. Improve your model generalisation thanks to data augmentation techniques and implement advanced methods to benefit from state-of-the-art architectures thanks to Transfer Learning methods.

Times-Series & Text data

Get comfortable into managing sequential data and text (sequence of words) by transforming them into appropriate inputs. Leverage the power of Recurrent Neural Networks to forecast future values and perform valuable Natural Language Processing.

Deep Learning made easy

Discover the Keras Deep Learning library which enables you to prototype easily while having the flexibility to tune precisely your neural network. Moreover, Google Colab will greatly speed up the computational time thanks to dedicated GPUs.

Machine Learning Pipeline

Move from Jupyter Notebook to a code editor and learn how to set up a machine learning project in the right way in order to quickly and confidently iterate. Learn how to convert a machine learning model into a model with a robust and scalable pipeline with sklearn-pipeline using encoders and transformers.

Machine Learning workflow with MLflow

Building a machine learning model from start to finish requires a lot of data preparation, experimentation, iteration, and tuning. We'll teach you how to do your feature engineering and hyperparameter tuning in order to build the best model. For this, we will leverage a library called MLflow.

Deploying to production with Google Cloud Platform

Finally, we'll show you how to deploy your code and model to production. Using Google Cloud AI Platform, you'll be able to train your model at scale, package it and make it available to the world. Cherry on top, you will use a Docker environment to deploy your own RESTful Flask API which could be plugged into any front-end interface.

Solve real-world problems with Data!

The final weeks of the course will culminate in the delivery of your capstone project! Working collaboratively in small teams, the project will allow you to utilise all the skills you have learned throughout the bootcamp in order to solve a real world data science problem.

  • Collaborate efficiently in teams of 3-4 people on a real data science project through a common Python repository.
  • Use a mix of your own datasets (if you have any from your company / non-profit organisation) and open-data repositories (Government initiatives, Kaggle, etc.)
  • Put into practice all the tools, techniques, and methodologies covered in the Data Science Course.
  • Invent, pitch, design, code, and deploy your fully functioning Data Project, to be used in real-life scenarios and as a portfolio-ready application to showcase your new data science skill set.

Admission & prep work

Admission & prep work

Our Data Science course requires a basic level of Python & Mathematics. As we want all of our students to succeed, you'll be able to test your level and refresh your skills before the Bootcamp starts.

Admission prerequisites in Python & Maths
  • Python prerequisites

    You'll need to be comfortable with data types & variables, conditions, loops, functions and data structures (List & Dictionary).

  • Mathematics prerequisites

    You'll need a High School level of Maths, meaning you will be comfortable with functions, derivatives, and systems of linear equations.

  • Testing your skills

    After a chat with our Admissions team, you will receive a Python & Mathematics Quiz to help you and the Admissions team better understand your current level in Python & Maths. We'll also provide you with a set of additional free learning resources to help you match the prerequisite level for the Bootcamp.

Post-admission prep work

Once you have been accepted onto the Data Science Bootcamp (congrats!), you'll receive ~ 40h of online learning resources. We require all of our students to complete this before the Bootcamp starts, either at their own pace or during our Data Prep Week.

The Data Prep Week takes place the week before the official start date of the Bootcamp. This is an additional week of interactive online learning designed to help you get through this content as efficiently as possible and ensure you have the necessary foundations in Python before the bootcamp starts.

Typical day

A typical day at Le Wagon Lausanne

From morning lectures to evening talks, every day in Lausanne is action-packed.

  • 08:30 Lectures
  • 10:00 Challenges
  • 15:30 Yoga
  • 16:30 Recap
  • 17:30 Events 19:30
Lectures
Lectures08:30 - 10:00

Grab a coffee and start every morning with an engaging & interactive lecture, before putting what you’ve learnt into practice.

Challenges
Challenges10:00 - 15:30

Pair up with your buddy for the day, and work on a series of programming challenges with the help of our teaching staff.

Yoga
Yoga (Optional)15:30 - 16:30

Learning to code can be very intense. If you want, you can make the most of the yoga classes we organize on certain days to relax and take a break.

Live code
Recap16:30 - 17:30

Review the day’s challenges and get an overview of upcoming lessons during live code sessions.

Talks & Workshops
Events (Optional)17:30 - 19:30

Be inspired and get priceless advice from successful entrepreneurs invited for exclusive talks.

Career week

Career Week

At the end of the bootcamp, we will organise our Career Week. This week gives you the tools you need to take the next steps in your career, whether it is finding your first job in a Data Science role, exploring career opportunities with your new data skill set, or launching your start-up.

Workshops Workshops

Benefit from a combination of panel discussions, workshops, presentations, and assignments to help you find the right career path.

Becoming job-ready Becoming job-ready

Prepare your personal profile, complete job applications, prepare for technical challenges, and make a game plan for after the bootcamp!

Inspiration Inspiration

Hear from alumni about their post-Bootcamp journeys and what a typical day looks like in their new careers.

Custom-made Custom-made

You can join any workshops or watch any tutorials that you are interested in. You create your own career week according to your interests and objectives

Timetable for the week
Monday
  • Discover career paths
Tuesday
  • Prepare for a job application
Wednesday
  • Prepare for technical challenges
Thursday
  • Apply for jobs
Friday
  • Game plan post bootcamp
Teachers

Passionate teachers

Since day one, we’ve taken teaching seriously. Great teachers inspire us to connect to topics on a profound level. Experience as a developer alone doesn’t necessarily make one an effective teacher — that’s why we’re passionate about finding not only great engineers, but deeply committed, experienced teachers.

Sinan Ucak
Sinan Ucak

Sinan is Product Owner for a Startup in Lausanne. He is an engineer and did the bootcamp in 2019. He keeps on developing web projects during his spare time.

more about Sinan
Community & tools

Network and learning platform

Lausanne's Data Science course is just the beginning of the journey. Once you graduate, you belong to a global tech community and have access to our online platform to keep learning and growing.

Slack icon Slack groups

Get tips and advice from professional data scientists & data analysts, access exclusive job and freelance opportunities from entrepreneurs & developers.

Online classroom

Access our online education platform at any time after the course: you will find all data science lectures, screencasts, challenges and flashcards.

Tech community

Benefit from our global community of 13,781 alumni working in data-related roles, but also entrepreneurs, developers and product managers all over the world.

Icon tutorials Global presence

Our different courses are running in 44 campuses all over the world: wherever you go, you belong to the Le Wagon community!

Community and tools for life
Career services

Find a data job in the best business & tech companies in Lausanne

Once the course ends, you benefit from our career services. We help you meet with the best recruiters in Lausanne and connect with relevant alumni.

microsoftwordCreated with Sketch. Career Playbook

Access a complete guide to kick-start your Data Science career in Lausanne after the course: boost your portfolio, find your dream job, leverage on our 13,781 alumni community.

myspaceCreated with Sketch. Career Events

Attend our job fairs and networking events, meet with the best tech companies and receive offers by recruiters looking for talent in data-related roles.

buymeacoffeeCreated with Sketch. Alumni Coaching Sessions

Our Data Science Course alumni love to share their experiences with more recent graduates. They explain how Le Wagon helped them find their dream role in Data Science and share insights into how they used their new data skill sets to accelerate their careers in various sectors, such as marketing, finance, healthcare and academic research.

wechatCreated with Sketch. Career Intros

Our local teams know their alumni and hiring partners, what they are up to and what they are looking for. They introduce you to the right people depending on your goal.

Our web development course alumni get hired by the best companies
Student outcomes

Where our alumni work in data in Lausanne

The best companies partner with Le Wagon and hire our alumni as Data Scientists, Data Analysts, Product Managers or Data Engineers.

Getaround Hired 6 graduates
+4
ContentSquare Hired 1 graduates
Aircall Hired 3 graduates
+1
Doctolib Hired 9 graduates
+7
Google Hired 5 graduates
+3
Frichti Hired 1 graduates
Financing options

Find the right financing option for you

Find out if you are eligible for special offers in Lausanne.

Swiss Aid for the Mountains
Swiss Aid for the Mountains

Get 50% off the bootcamp cost if you workin a small company (less than 49 full time employees) located in the Mountains (at least zone 2) thanks to the Swiss Aid for the Mountains.

Check if you can benefit from the Aid
1000 CHF for employees
1000 CHF for employees

You can get 1000 CHF thanks to the #lifelonglearning Boost program. A program co developed by Digital Switzerland & UBS. 2 important conditions: you have to be employed and your employer has to contribute to the training too.

More info
Professional reconversion with AI
Professional reconversion with AI

If you are a AI beneficiary, you can ask them to finance the whole bootcamp to help you reconvert professionally. The AI fund can also continue to pay your daily indemnities and pay for transport and food.

The most acclaimed Data Science Bootcamp and courses

Le Wagon is the #1 ranked coding bootcamp on Switchup Coursereport logo

Le Wagon has 2200 reviews with an average grade of 4.98/5 which makes it the most acclaimed coding bootcamp worldwide on Switchup according to student reviews! Whilst these reviews make us proud, above all they make us happy. Behind these reviews are hundreds of people around the world who have had a life-changing experience joining our program, which has opened new doors for them. We feel blessed and honoured to have enabled them - and to keep enabling our students - to become autonomous in coding, upskill or change their career, or launch their own startups.

Also, these 2200 reviews are extremely important for us to make sure we’re always meeting the same level of excellence. Having such positive and enthusiastic reviews about our bootcamps is the ultimate proof that we provide the best tech education for all our students, in the 44 cities we run our coding bootcamps in.

Campus Le Wagon Lausanne

Le Wagon Lausanne - Coding School

Data Science course in Lausanne
Le Wagon Lausanne - Coding School
Rue de Lausanne 64, 1020 Renens

FAQ

Any questions about our program in Lausanne

If you got here, it means that you have questions about Le Wagon: how to apply, who can join, what you’ll learn… Good! We have the answers.

Where should I do Le Wagon?

We always advise our students to study in the city where they plan to settle down in the future.

At Le Wagon, you will learn new skills, but you will also develop your personal network, with other students and alumni. You will also be exposed to the local Tech ecosystem and benefit from the links built between Le Wagon and local companies, startups, incubators, etc...

Is there a certificate after completion of the bootcamp?

Le Wagon delivers a certificate of completion for the students who followed the bootcamp seriously and completed the daily exercises and projects.

Le Wagon in Lausanne is certified by Eduqua, a high quality label for schools in Switzerland (Certificate #18688-43). However, the Le Wagon certificate is not yet recognized officially by the Swiss authorities.

How many students in Lausanne?

Our batches average 12 students in Lausanne. It is a great opportunity to benefit from personalized teaching and tight relationship with other students. This number keeps growing batch after batch.

How can I come to Le Wagon everyday?

🚃 By train, the easiest is to stop at Renens station and take the bus (5 min) or walk (10 min) to Le Wagon. It is also possible to stop at Malley station.

🚎 By bus, lines 17 & 19 will drop you right at Le Wagon. Lines 32 & 33 also stop closeby.

🚗 By car, we can arrange parking spots. Spots cost 150 CHF for the bootcamp. It is better to ask in advance to secure a spot.

Le Wagon Lausanne on Google Maps

What are the accommodation options?

We can arrange a room with a host family or in an apartment close to Le Wagon for about 600 CHF / month. It is better to ask in advance to secure accommodation.

What are the options for lunch / dinner ?

[Full-time] We are lucky to have a great restaurant in the building that serves 2 different menus each day made with local and fresh products. Price is 13.50 CHF for a menu.

Some students prefer to bring their own food and use the small kitchen area at Le Wagon (fridge and micro-wave). There are also supermarkets around.

[Part-time] We advise students to eat before/after the evening session or to bring something to eat with them.

Do I need to know programming?

Yes, a fair minimum. Our Data Science bootcamp is very intense and will jump into advanced topics from the very first week. Unlike our FullStack Web Development bootcamp where we spend 3 weeks learning Ruby from scratch, applicants for the Data Science bootcamp need some programming. How much? You must be comfortable with data types & variables, conditions, loops, functions and the two data structures list & dict (named Array and Hash in Ruby). If you know those topics in Ruby, JavaScript or some other language than Python, feel free to embark on those free Fundamentals & Intermediate courses before the bootcamp.

What are the payment terms?

[Full-time] The payment is made in 2 installments: 50% before starting the bootcamp and 50% around the middle.

[Part-time] The payment is made in 3 installments: 30% before starting the bootcamp, 40% around the middle and 30% just before the end.

What is the daily schedule in Lausanne?

[Full-time] A typical day starts at 8.30 and ends at 18.00. There is a lecture from 8.30 to 9.30, followed by exercises or projects, and a live-coding session from 16.30 until 18.00.

[Part-time] Please check the typical week schedule.

For both the Full-time & Part-time formats, lectures are maintained during bank holidays, unless stated in the training contract. There is a 3 weeks break during Xmas holidays for the Part-time.

Are there events organized in Lausanne?

Once a week on average, an event is hosted at Le Wagon, and students are more than welcome to join. It usually takes place from 18.30 to 20.00 and it is a good opportunity to meet people working in Tech locally.

Find all our events here

Is there also Yoga in Lausanne?

Yoga lessons are not set yet in Lausanne. However, we advise students to take breaks regularly because days are intense 😅

In which language do we teach?

In Lausanne, we teach in French.

For more questions & answers, you can visit our FAQ section! If you would like to discuss with Le Wagon team, don't hesitate to contact us.

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Want to go further?

Next Lausanne Data Science course (full-time coding bootcamp) starts on Apr 11, 2022

Apply now
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